摘要
采用扩展卡尔曼滤波法(Extended Kalman Filter,EKF)进行电池系统荷电状态估计时存在计算复杂、精度不高的问题。以并联型电池系统为研究对象,结合并联型电池系统空间状态方程,采用无迹卡尔曼滤波法(Unscented Kalman Filter,UKF)对并联型电池系统进行荷电状态估计。在脉冲工况下,UKF与EKF算法的仿真与试验数据匹配情况的分析结果验证了UKF算法的准确性和高鲁棒性。
Extended Kalman Filter（EKF） method is used to estimate the state of charge（SOC） of battery system,yet problems of computational complexity and lower accuracy arise. Comparatively Unscented Kalman Filter（UKF） is then used to estimate SOC of parallel battery system considering its state space equation. The stimulated estimation and experimental results obtained through EKF and UKF methods are compared and analyzed,which verifies the accuracy and robustness of the proposed UKF calculation.
出处
《江苏工程职业技术学院学报》
2015年第4期12-14,共3页
Journal of Jiangsu College of Engineering and Technology
基金
江苏省自然科学青年基金(编号BK20150430)
江苏省高校自然科学研究项目(编号15KJB480004)
关键词
并联型电池系统
荷电状态估计
无迹卡尔曼滤波法
parallel battery system
state of charge estimation
Unscented Kalman Filtering
